Cost vs Efficiency: Optimizing Urban Building Energy Consumption, a Case for Ahmadabad

The Central Business District (CBD) of Ahmedabad in India, planned to be developed by 2040, will have an increased floor space, five times of what it is in 2020. This will double the cooling energy demand if contemporary practices are followed. Moreover, the Energy Conservation Building Code, 2017 (ECBC) of India, despite its launch in 2007, has not been ratified in many states. With the ECBC prescriptive guidelines tailored according to the local and regional priorities, a suitable trade-off between energy efficiency and the lifecycle cost of the Energy Conservation Measures (ECMs) can be established. Thus, performing Urban Building Energy Modelling (UBEM) can help urban planners and local governments to implement the code and improve the performance of both the existing and the upcoming building stock.

This paper aims to develop building envelop retrofit strategies which minimizes the lifecycle cost and the total annual cooling energy consumption in the coming decades, till 2040 with a rise in floorspace for the CBD of Ahmedabad. For this, the UBEM of 0.7 sqkm of the CBD, is developed for 2020, 30 & 40 using the existing dataset available with Ahmedabad’s local authority. The buildings are characterised into six archetypes based on their uses i.e. Residential, commercial, retail, healthcare, hospitality and educational. Different building types have different operational patterns, equipment, lighting, air conditioning loads and vintage. Thus, the envelop retrofits will also respond differently to these archetypes and be greatly affected by the building’s adjacencies, and the mutual shading from neighbouring structures.

The cost vs energy optimization is performed using the modeFRONTIER software coupled with the EnergyPlus simulation engine for 2020, and the savings are projected till 2040. Five envelop properties including glazing Solar heat gain coefficient (SHGC), wall and roof insulation and roof reflectance are selected for the parametric study with range of values prescribed within augmented stringency of ECBC. A Design of Experiments (DOE) developed by the Uniform Latin Hypercube (ULH) is performed with 90 iterations on all the buildings. To minimize computational effort, the Response Surface Method (RSM) based virtual optimization is carried out by training 80% of the DOE results, the algorithm selected is based on the convergence accuracy and judged using least R-squared method with the Stepwise Regression algorithm giving an accuracy of 98% when validated with the results from the solver. The sensitivity analysis indicated that the SHGC of the Office building’s glazing contributes to 70% of the total cooling energy consumption, followed by roof insulation and reflectance. Thus, shading the windows and roof and improving the glazing specification are the most cost-effective strategies. With the selected set of ECMs, there is a potential of 20% reduction in the total cooling energy.